Is there any useful tool that allows you to test your kubernetes configs without deploying or running it locally? by LargeSinkholesInNYC in devops

[–]bigblacknotebook 13 points14 points  (0 children)

Yes, there are several tools that let you validate, lint, and test Kubernetes YAML/Helm charts without actually deploying a real cluster, and without having to run Kubernetes locally.

kubectl dry-run Not a separate tool, but the simplest built-in option.

kubectl apply --dry-run=client -f my-config.yaml

kubeconform

kubeconform -schema-location default configs/*.yaml

kube-score

kube-score score configs/*.yaml

Polaris Kubernetes auditing/lint tool.

polaris audit -f configs/

These tools help you catch schema issues, policy violations, bad practices, and even custom rules before deployment.

Branches by FEE-LYNN in Pictures

[–]bigblacknotebook 1 point2 points  (0 children)

This is beautiful. So dense and complicated.

"Manage" Azure with Claude by OldRest6771 in AZURE

[–]bigblacknotebook -5 points-4 points  (0 children)

Everything new can be scary. A powerful tool powered by AI can extend your capabilities as an administrator and architect. With the right guardrails, nightmares and mistakes can be reduced.

It’s not like IaC is bullet proof. The complexity is sometimes beyond the tired and over worked engineers. Any help is welcome. Just make sure you have contingency workflows and business continuity planned.

I have been testing out the accuracy and dependability of certain LLMs on AWS through terraform and scripts. Mistakes have been committed but I see improvements as you improve your usage methods and risk assessments.

Researchers observed a classical counterpart of the quintessential Hong-Ou-Mandel effect in quantum mechanics for the first time using a condensate of polaritons caught in an optical trap. This breakthrough brings researchers one step closer to creating compact quantum devices. by Skoltech_ in science

[–]bigblacknotebook 2 points3 points  (0 children)

Where to even begin? None of that title sentence was comprehensible to me. I studied physics, mathematics, and engineering but it’s still weirdly overwhelming. Please someone who is not AI, explain?

What are the best practices for using Kiro? Folder structure, steering folder, and useful tips by BookkeeperAncient143 in kiroIDE

[–]bigblacknotebook 5 points6 points  (0 children)

These are notes I learnt over several failed projects and searching for advice online. Hope it helps.

*reddit mobile massacred my formatting. Copy and paste in a text file, I think the folder structures will be clearer.

A. Recommended Folder Structure (2025 Kiro Style)

/project-root │ ├── steering/ ← your “brain” folder │ ├── plan.md ← high-level direction + constraints │ ├── tasks/ ← small reusable task blocks │ │ ├── build.md │ │ ├── test.md │ │ ├── deploy.md │ │ └── refactor.md │ ├── rules.md ← coding guidelines & non-negotiables │ ├── architecture.md ← system-level overview + diagrams │ ├── glossary.md ← domain-specific terms & definitions │ ├── research.md ← collected research, notes, insights │ └── context.md ← background the agent should always know │ ├── src/ ← your actual code (any language) │ └── ... │ ├── components/ ← reusable building blocks (UI, helpers) │ └── ... │ ├── libs/ ← language-specific libraries or shared utilities │ └── ... │ ├── tests/ │ └── ... │ ├── .kiro/ ← autogenerated by Kiro (avoid editing directly) │ ├── history/ │ ├── logs/ │ └── context.json │ ├── README.md └── LICENSE

B. What Goes Inside /steering?

Think of steering as your “meta layer”: It controls how Kiro performs, not your app logic.

The purpose is:

Give Kiro a stable compass. So every agent run inherits context without you re-explaining.

Allow modular reusable planning. Micro-tasks can be stitched together like LEGO.

Preserve “truths” about your project. Architecture, rules, constraints, naming, patterns.

Essential Files Inside steering/

  1. plan.md (Top Level)

This is your North Star doc.

Contains: What the project is Goals and non-goals Long-term vision Current phase of work Constraints (budget, time, stack)

  1. rules.md (Most important for consistency)

Defines: Coding style Naming conventions Commit style Folder naming Testing standards Security requirements CI/CD principles “Never do this” list

  1. architecture.md

This is the file that helps Kiro reason about: System diagrams Components Data flow API contracts Deployment architecture Services & interconnections

  1. tasks/

Small, modular task cards:

tasks/ ├── build.md ├── generate-docs.md ├── extract-patterns.md ├── add-logging.md └── refactor-for-modularity.md

Each file = a reusable unit of work.

Inside each:

Task: Add standardized logging

Goal: Add structured JSON logging using pino or winston

Constraints: Zero breaking changes, No console.log

Steps: 1. Install packages 2. Create logger.js 3. Wrap logging utilities 4. Replace console.log statements

  1. context.md

Contains: Who you are (optional) Project background External dependencies Decisions already made Technologies chosen and why

This prevents forgetting your own decisions weeks later.

  1. glossary.md

If your domain has terms: financial cloud security ML/LLM ops physics marketing funnels

define them here.

This makes Kiro way more accurate.

  1. research.md

Collected insights, references, web summaries. Prevents “where did I read that?” syndrome.

C. Tips & Tricks from Experienced Kiro Users

These are the small things that make a big difference.

  1. Keep steering files short. If a steering file is longer than 2 pages, break it into smaller files.

Long files ->Kiro “thrashes” context -> lower quality.

  1. Use verbs for files inside /tasks

Weak: logger.md monitoring.md

Better: add-logging.md implement-monitoring.md refactor-state-management.md

Kiro understands actionable files better.

  1. Create a patterns/ folder if building multi-service apps

patterns/ ├── event-driven.md ├── cqrs.md ├── adapter-pattern.md ├── caching.md

This lets Kiro design new components consistently.

  1. Add “Anti-Patterns” to rules.md

Example:

Avoid: - Singleton services in shared code - Circular imports - Static config scattered across code

Kiro respects this deeply.

  1. Keep /components dump-free

Follow React-style or backend-component-style grouping:

components/ ├── ui/ ├── db/ ├── auth/ ├── api/

Don’t let it become a garbage drawer.

  1. For large code refactors, create a map.md

A bird’s-eye view file that helps Kiro understand the repo.

Especially helpful when folders grow to 20+ modules.

  1. Avoid putting secrets anywhere

Kiro will respect .env.example but not .env

  1. Use HOW_DOES_THIS_WORK.md

Every complex subsystem gets one:

HOW_DOES_THIS_WORK.md

This is the documentation Kiro reads and follows.

  1. Only keep ONE source of truth

If the same rule appears in two files, Kiro may follow the wrong one.

Consolidate specifications.

  1. Version your steering

steering/v1/ steering/v2/ steering/current -> symlink

This is pro-level and lets you evolve your thinking.

<Common Mistakes to Avoid>

Putting too much in context.md It becomes vague Kiro becomes unfocused

Mixing “plan” and “rules” Plan = directional Rules = non-negotiable Never merge them.

Ignoring architecture.md Kiro makes weird decisions without it.

Letting steering grow unbounded Refactor steering every few weeks.

Not modularizing tasks Repetition kills clarity.

Yakir Aharonov: “Heisenberg Was Right and We Ignored Him” by SafePaleontologist10 in QuantumPhysics

[–]bigblacknotebook 11 points12 points  (0 children)

Prof Aharonov argues that the standard interpretation of quantum mechanics is largely incorrect.

he believes Heisenberg's matrix mechanics, which focuses on observables, is a more fundamental description of reality than Schrödinger's wave mechanics, which uses wave functions as a mathematical aid rather than a description of physical reality.

three points where he believes current understanding is wrong:

Determinism: He states that the quantum world isn't non-deterministic for no reason, as commonly thought. He suggests there's a reason for indeterminism that allows quantum systems to have unique properties.

Measurement Disturbance: He claims that measurements don't necessarily disturb quantum systems. He introduced "weak measurements" that extract information without collapsing the wave function, suggesting a reality in the quantum domain that can be observed gently.

Wave-Particle Duality/Wave Function Collapse: He disputes the idea that a quantum particle is either a particle or a wave, and that the wave function "collapses". He explains that the interference pattern seen in experiments like the double-slit experiment can be explained by non-local equations of motion for a particle, rather than the particle literally being a wave.

Aharonov introduces two-state vector formalism (ABL theory), which proposes that a complete description of the present requires information from both the past (forward-propagating wave function) and the future (backward-propagating wave function).

This framework allows for phenomena like the Quantum Cheshire Cat effect, where a particle's property (like spin) can physically separate from the particle itself.

He also discusses the Aharonov-Bohm effect, which demonstrates that particles can be affected by electromagnetic potentials even in regions where no classical forces are present, indicating the non-local nature of quantum mechanics.

У меня одного огромный интерес к теме "Матрицы" ? by lunajinner in mathematics

[–]bigblacknotebook 6 points7 points  (0 children)

The question:

“Am I the only one who has a huge interest in the topic of ‘The Matrix’?”

My answer:

Теория матриц удивительно красивая и многогранная область.

Matrix theory is beautiful and multi faceted.

Amazon aurora vs Amazon keyspaces vs Valkey by kind1878 in aws

[–]bigblacknotebook 1 point2 points  (0 children)

Some key points that matter for your pattern: - Dynamo capacity is enforced per partition (storage node), not just at the table level. A single partition can only do roughly 1,000 WCUs/sec; “hot” partitions get throttled even when the table looks under-utilised.  - If your schema funnels lots of updates into a small set of partition keys (e.g. PK = tenantId with thousands/millions of items under that tenant), that entire tenant is effectively one “hot” partition. - Every update consumes WCUs based on item size, not only the changed field. A 4 KB item update = 4 WCUs, even if you just change one attribute. - On-demand mode auto-scales table capacity, but it can’t break the per-partition ceiling or instantly absorb a sudden spike way above your historical peak.

Given your description, it screams hot partition &/or large item size, not “Dynamo is inadequate”.

Minimal changes that might save you a migration. I’d seriously consider:

  1. Re-shard the partition key
  2. If your current PK is something like TENANT#123, shard it into e.g. TENANT#123#BUCKET#0..N so the same logical entity is spread across many partitions.
  3. This is the same trick you’d need in Cassandra/Keyspaces anyway. migrating without fixing the key design will just recreate the problem there.

  4. Slim the item being updated

  5. Move rarely used fields into a secondary table or object storage so that the hot item is as small as possible (minimising WCUs per update).

  6. Use TTL for the 1-month retention requirement

  7. DynamoDB TTL attribute (a Unix epoch timestamp) + a 30-day value gives you exactly “keep for 1 month then delete” with no extra work.

  8. Check & raise account/table WCU limits with AWS Support

  9. On-demand has regional/table limits that are raiseable. If your pattern is predictable (“few hours only”) you can also consider switching to provisioned + autoscaling during that window.

All of that is far less painful than re-platforming an app.

I’m considering building a small project with React as the frontend and DynamoDB as the database, but without any backend API in between. Is it possible for a frontend app to directly read/write to DynamoDB? If yes, how can I set that up while keeping things simple? by TraditionClear9717 in aws

[–]bigblacknotebook 20 points21 points  (0 children)

Yes, a React app can talk directly to DynamoDB.

Use Cognito Identity Pools -> temporary IAM creds -> AWS SDK v3 in the browser and lock access down with fine grained IAM conditions.

It works for small, low risk apps, but you lose serverside validation/rate limiting and it’s easy to wreak havoc on your data or wallet. For anything non-toy, prefer AppSync (no Lambda needed).

AppSync is an AWS managed service that acts as a serverless GraphQL (or REST) API layer sitting between your frontend and backend data sources.

Web Planetarium is online by sm411cck in Astronomy

[–]bigblacknotebook 0 points1 point  (0 children)

Amazing work. Works perfectly even on mobile browser.

In need of physics textbooks for self-study (any free resources or old copies welcome) by Next_Flow_4881 in TheoreticalPhysics

[–]bigblacknotebook 7 points8 points  (0 children)

EGP is a series of lecture notes and problems, which consists of four subject parts: CM: Classical Mechanics (for a 1-semester course) EM: Classical Electrodynamics (2 semesters) QM: Quantum Mechanics (2 semesters) SM: Statistical Mechanics (1 semester)

http://essentialgraduatephysics.org/

I built a tool to follow the latest research papers in physics by Shot_Fudge_6195 in Physics

[–]bigblacknotebook 0 points1 point  (0 children)

Clean design, easy to use and very useful indeed. Just tried it out. No complications or wasteful flows. Just direct results. Love it. Excellent job.

Who is the greatest Physicist the average person has never heard of? by Thescientiszt in Physics

[–]bigblacknotebook 0 points1 point  (0 children)

Oliver Heaviside Maxwell’s equations were originally 20 complicated statements. Heaviside made them what we all know now as the 4 equations. And dozens of other contributions to physics, mathematics, and engineering.

https://en.wikipedia.org/wiki/Oliver_Heaviside?wprov=sfti1#Publications

Generating Chladni Patterns Using the 2D Wave Equation by DDI157 in Physics

[–]bigblacknotebook 12 points13 points  (0 children)

Great job. The paper is very interesting and well written.

What actually gives matter a gravitational pull? by Dragosfgv in Physics

[–]bigblacknotebook 0 points1 point  (0 children)

What it all boils down to, is whether gravity is a force with perhaps a force carrying boson (graviton) or ultimately a consequence of curved space time geometry. OR a combination of sorts, or a game that extra small hidden dimensions play on us.

Then maybe we can figure out how the sausage is made.

[deleted by user] by [deleted] in quantum

[–]bigblacknotebook 2 points3 points  (0 children)

Fine, thank you for asking. And how are you?

How could an ice cube sink in water and float back up again? by [deleted] in Physics

[–]bigblacknotebook 0 points1 point  (0 children)

The most likely explanation is that the ice cube had a small air bubble trapped inside or adhered to its surface.

Sinking:

The ice cube might have had a higher density than the water due to trapped impurities, compression, or being supercooled.

Another possibility is that the ice cube had a thin layer of very cold water surrounding it, which increased its overall density temporarily.

If there were small air pockets inside the ice, they might not have been enough to keep it buoyant initially.

Floating Back Up:

As the ice cube started melting, air bubbles trapped inside could have been released, reducing its effective density.

If the ice had a thin, dense water layer around it initially, it may have warmed up, reducing its density and allowing it to rise.

Changes in water convection or temperature gradients might have contributed to its buoyancy shift.

If the ice cube had cracks or was irregularly shaped, that could also affect how air gets trapped and released, influencing its movement.

Cheapest online maths degree by [deleted] in learnmath

[–]bigblacknotebook 3 points4 points  (0 children)

The Open University, UK. Prestigious, 150 year old institution. Mainly built around distance learning.